Genie can only answer based on the data it can query. When data is modeled only as flat tables, important context is often missing: how customers, accounts, transactions, products, suppliers, assets, or events relate to one another.

Neo4j adds that context by analyzing connected data from Delta Lake to uncover relationships, communities, paths, and patterns. Those graph insights can then be written back to Databricks as ordinary dimensions, such as connected scores, community labels, and relationship signals.

In this on-demand webinar, you’ll see the pattern in action through a live financial crime investigation. The demo shows how Neo4j enriches Delta Lake data so Genie can deliver more contextual, relationship-aware answers using natural language.